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Cuda Jobs (NOW HIRING)

Nvidia

Senior DL Compiler Engineer- CUDA Tile

Austin, TX · On-site

$121K - $160K/yr

CUDA Tile shipped with CUDA 13.1 and is a major addition to CUDA ( * You will design and implement compiler transformations, develop MLIR-based dialects and lowering passes, and optimize the ...

Nvidia

OR

$122K - $161K/yr

CUDA Tile shipped with CUDA 13.1 and is a major addition to CUDA ( * You will design and implement compiler transformations, develop MLIR-based dialects and lowering passes, and optimize the ...

Nvidia

OR

$122K - $161K/yr

CUDA features improve both productivity and performance of AI applications. Your work in AI toolkits will accelerate enabling those for the community. This is an outstanding opportunity for someone ...

Dalcom LLC

C++/CUDA-Signal Processing Engineer

Aberdeen, MD · On-site

$140K - $176K/yr

C++/CUDA Signal Processing Engineer Company: Dalcom Engineering Location: Aberdeen Proving Ground, MD Salary: $140,000-$176,000 Position Overview: Dalcom Engineering is currently seeking a software ...

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How much do cuda jobs pay per year?

As of Jun 7, 2026, the average yearly pay for cuda in the United States is $200,510.00, according to ZipRecruiter salary data. Most workers in this role earn between $205,000.00 and $205,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced when working as a CUDA Developer, and how can they be addressed?

CUDA Developers often encounter challenges such as debugging complex parallel code, optimizing memory usage, and ensuring compatibility across different GPU architectures. To address these, it's important to leverage profiling tools like NVIDIA Nsight to identify bottlenecks and inefficiencies. Collaborating closely with team members, such as data scientists and software engineers, can also help in resolving integration issues and achieving better performance. Staying updated with the latest CUDA Toolkit releases and best practices is key to overcoming these challenges and delivering robust GPU-accelerated applications.

What are the key skills and qualifications needed to thrive as a CUDA Developer, and why are they important?

To thrive as a CUDA Developer, you need strong programming skills in C/C++, a solid understanding of parallel computing concepts, and experience with GPU architectures. Familiarity with the CUDA toolkit, NVIDIA GPUs, and related profiling/debugging tools is typically required, and certifications in GPU programming can be advantageous. Analytical thinking, problem-solving, and effective communication are essential soft skills for optimizing code and collaborating with cross-functional teams. These skills are crucial for developing high-performance applications that leverage GPU acceleration, ensuring efficiency and innovation in compute-intensive fields.

What is the difference between Cuda vs GPU Developer?

AspectCudaGPU Developer
Required CredentialsKnowledge of CUDA programming, often with a background in computer science or engineeringExperience with GPU programming, CUDA, OpenCL, or similar; often requires a degree in computer science or related fields
Work EnvironmentPrimarily focused on developing and optimizing CUDA-based applications for NVIDIA GPUsDesigning, developing, and maintaining GPU-accelerated applications across various platforms and hardware
Industry UsageUsed mainly in high-performance computing, AI, and scientific research involving NVIDIA GPUsApplied across gaming, scientific computing, AI, and multimedia industries

In summary, CUDA is a specialized skill set focused on programming NVIDIA GPUs using CUDA, while a GPU Developer has a broader role that may include using various GPU programming tools and working across multiple platforms. CUDA is a subset of the skills a GPU Developer might possess, making them closely related but distinct roles.

What is a Cuda job?

A CUDA job typically involves developing, optimizing, and implementing parallel computing applications using NVIDIA's CUDA platform. CUDA (Compute Unified Device Architecture) enables developers to leverage the power of GPUs for high-performance computing tasks such as deep learning, simulations, and scientific computing. Professionals in this role often work with C, C++, or Python, using CUDA libraries and frameworks to accelerate processing. Strong knowledge of parallel programming, memory management, and GPU architecture is essential for success in this field.

What are CUDA developers?

CUDA developers are software engineers who specialize in using NVIDIA's CUDA (Compute Unified Device Architecture) platform to write programs that run on Graphics Processing Units (GPUs). Their primary focus is on parallel computing, optimizing algorithms to leverage GPU acceleration for tasks such as scientific computing, machine learning, and data processing. These professionals typically have strong skills in C, C++, and Python, and a solid understanding of GPU hardware. CUDA developers are in demand in industries that require high-performance computing solutions.

How much do CUDA programmers make?

CUDA programmers, who develop software using NVIDIA's parallel computing platform, typically earn between $80,000 and $130,000 annually depending on experience, location, and industry. Senior roles or those with specialized skills in GPU optimization and machine learning can earn higher salaries, especially in tech hubs or large companies.
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Cuda jobs near you
Infographic showing various Cuda job openings in the United States as of May 2026, with employment types broken down into 98% Full Time, 1% Part Time, and 1% Contract. Highlights an 87% Physical, 6% Hybrid, and 7% Remote job distribution, with an average salary of $200,510 per year, or $96.4 per hour.

CUDA Senior Developer ( Mathematical Mindset/ New Grads

Ktek

Dallas, TX • On-site

Full-time

Posted 21 days ago

Job description

Position/ TITLE: CUDA Developers Junior to senior & Lead Level ( Mathematical Mindset/ New Grads)
Location : New yOrk, NJ, Dallas TX, Florida
Open for Fulltime & Contract
Please share resumes at Chandra.reddy@ktekresourcing.com

Who are we looking For:
We are seeking talented individuals with 3 to 8 years of experience who are passionate about mathematics and eager to learn CUDA programming to join our innovative team. While previous CUDA experience is beneficial, it is not mandatory to prioritize strong mathematical abilities, analytical thinking, and enthusiasm for learning and growth in high-performance computing.
Key Responsibilities
Learn and apply CUDA programming principles to develop and optimize GPU-accelerated applications.
Good team player who will work with team to contribute to design. He will work to implement, and debug parallel algorithms.
Analyze performance bottlenecks and optimize computations for maximum efficiency.
Document code, algorithms, and procedures clearly for internal and external stakeholders.
Technical Skills Must Have
Strong mathematical foundation in areas such as linear algebra, calculus, numerical methods, or statistics.
Proficiency in at least one programming language (C++, Python, or similar).
Excellent problem-solving skills and logical reasoning capabilities.
Ability to learn quickly and adapt to new technologies.
Technical Skills - Good to have
Familiarity with parallel computing concepts.
Exposure to GPU programming (CUDA/OpenCL).
Having Worked in Cuda Frameworks like RAPIDS, cuDF, cuTensor, PyTorch, TensorFlow is a plus.
Experience with scientific computing, numerical simulation and/or linear programming.
What We Offer
Opportunity to gain expertise in cutting-edge CUDA technology.
Supportive learning environment with mentorship from experienced CUDA developers.
Competitive salary and benefits.
Flexible working conditions (including remote work options).
Mphasis is an equal-opportunity employer. We value diversity and encourage candidates from all backgrounds to apply.
Application
Interested candidates should submit their resume and a brief statement highlighting their mathematical expertise, programming skills, and interest in CUDA development.
Please apply along with your answer to the following problem. Any application without an answer to the problem will not be entertained.
Mathematical Challenge:
Include your proposed approach or insights on the following linear algebra problem in your application:
'Given a very large sparse matrix, propose an efficient algorithm or method to quickly identify if the matrix is singular or invertible without performing full matrix inversion.'
Preferred Qualifications:
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
A portfolio showcasing CUDA experience.
Process Skills:
General SDLC processes
Understanding of utilizing Agile and Scrum software development methodologies
Skill in gathering and documenting user requirements and writing technical specifications.
Behavioral Skills:
Work closely with designers, Architects, data scientists, product managers, and other engineers to deliver comprehensive solutions.
Strong problem-solving skills, with a creative approach to tackling complex challenges.
Communicate effectively and share technical knowledge with the team.
Be open to feedback and continuously learn and adapt to new technologies.
Ability to work independently and as part of a team.
Passion for learning and staying updated on the latest technologies.
Good Attitude and Quick learner .
Certification (Good to have) :
Related to CUDA any certifications
AI/ML or Python certification.